Star formation is a chaotic process, involving the evolution and interaction of a wide variety of structures. The interstellar medium exhibits substructure over a range of scales, and the clusters which form from the densest parts of this material may be imprinted with this clumpy distribution. In this thesis, we describe and evaluate statistical tools for quantifying structures that are important to the star formation process, in order to constrain the underlying physics and robustly compare observations, simulations and synthetic observations. We describe the basic theory and some common applications of fractal theory in astronomy. We show that some common measures of fractal structure are inconsistent and that comparing values derived from different data types (e.g. continuum data of molecular cloud maps and discrete data of star distributions) can lead to confusion. We introduce the Q+ algorithm which quantities the substructure in star clusters in terms of a fractal distribution. We describe the derivation and validation of this method and apply it to observed and simulated data sets. We examine the possibility of applying this same analysis to continuum data by converting the greyscale image into a statistically representative distribution of points. We introduce the J plots algorithm which uses the principal moments of inertia of a two-dimensional pixelated structure to quantify its shape. We show that this can be used to identify the shapes of structures extracted from astrophysical images using dendrograms. We apply this method (i) to data from the Hi-GAL survey to demonstrate the identification of ring-like shapes, and (ii) to simulations of _lament formation to quantify the differences in structure resulting from the nature of turbulence in the accreting material.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:761325 |
| Date | January 2018 |
| Creators | Jaffa, Sarah |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/116134/ |
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